Much prior emphasis in research on Alzheimer's disease (AD) has been on genetic studies, which have uncovered the fundamental involvement of the APP, APOE and PS1 genes. But with the exception of polymorphisms in APOE, known coding variants in these genes are quite rare, and the existing data do not fully account for the heritability of late-onset AD (LOAD) in the general population. Additional chromosomal loci putatively influencing AD susceptibility have been uncovered by genome-wide association studies (GWAS) and related high-throughput genomic scans, but replication has been uneven and the causative or predisposing genes have not been clearly pinpointed. Further it has not been possible to gauge the importance of numerous sub-threshold statistical peaks in these scans. New approaches are needed to get through these roadblocks, and we believe that a combined strategy to first obtain lists of loci with sequence-dependent allele-specific methylation (ASM) and/or allele-specific mRNA expression (ASE) in human cerebral cortex, and then overlap this information with statistical peaks from GWAS, will help to solve this problem. We will screen for ASM/ASE in human cerebral cortex using microarray-based and sequencing-based methods. We will validate the strongest candidate loci for ASM/ASE using independent assays, and overlap the list of such loci with data from existing and ongoing GWAS in LOAD. Loci from the intersection of these 2 datasets will be subjected to highly focused and thus cost efficient genetic fine mapping in 3 independent well characterized cohorts of LOAD case and controls. Our reasoning is that sequence-dependent ASM/ASE in or near specific genes in the cerebral cortex will be a robust indicator for the presence of bona fide cis-acting regulatory polymorphisms (rSNPs, rCNPs) that confer inter-individual differences in the expression of specific genes in the human cerebral cortex, and that within this set of genes will be some that cause inter-individual differences in LOAD susceptibility. Reproducible signals from GWAS and related genome scans for LOAD that overlap with loci that show ASM and/or ASE will thus have a strong functional underpinning and warrant further intensive study as biological contributors and potential therapeutic targets in LOAD.